IJSRSET calls volunteers interested to contribute towards the scientific development in the field of Science, Engineering and Technology

Home > IJSRSET1626153                                                     


Development of Traffic Flow in a Mega City Using Neural Network Controller

Authors(4):

Eze M. N., Uchegbu C. E., Ilo F. U., Ugwu O. C.
  • Abstract
  • Authors
  • Keywords
  • References
  • Details
This paper focuses on improving vehicular traffic flow using neural network controller system. Such real time simulation software was currently used as a tool for optimizing the design of vehicular controls in traffic related matters. In this paper, field data were collected from Digital Security Company Enugu which included measurement from the average waiting time for the red light duration and different green light durations. The testbed environment is made up of a junction, ABCD. It was observed that the morning hour otherwise known as busy hour, more vehicles enters into the testbed environment through lane A and B while less vehicle queue in lane C and D respectively. With the introduction of neural network in the design, this will help in decongesting the vehicular problem both in the busy hour and less busy hour. This characterisation of testbed environment were neural network is used is not so with junctions where traditional traffic flow control is used, a lane with no vehicle on it is still has time allotted to it while those with long queues of vehicles are asked to stop and wait until they are asked to move.

Eze M. N., Uchegbu C. E., Ilo F. U., Ugwu O. C.

Traffic Flow, Artificial Neural Network, Traffic Light Management, Fixed Delay

  1. Abdul Kareem, E.I. & Jantan, A. (2011). An Intelligent Traffic Light Monitor System using an Adaptive Associative Memory. International Journal of Information Processing and Management. 2(2): 23-39.
  2. Al-Alawi, (2009). "Web-Based Intelligent Traffic Management System, Proceedings of the World Congress on Engineering and Computer Science (WCECS) Vol. 1 San Francisco USA.
  3. Albagul, A., Hraivi M and Hidayalthullah M.F., (2010) "Design and Development o Sensor Based Traffic Light System. American Journal of Applied Sciences Vol. 3, No 2 pp 1745-1749,
  4. Bank, J., J.S et al (2000). Discrete Event System Simulation, 3rd Ed., Prentice-Hill.
  5. Chattaraj, A. et al, (2008). Intelligent Traffic Control System using In Proceedings of the National Conference on Device, Intelligent System and Communication & Networking, India.
  6. Ezell, S. (2011). Explaining IT Application Leadership: Intelligent Transportation System. White Paper of the Information Technology and Innovation, (ITIF).
  7. Fathy, M. and Siyal, M.Y (1995). Real-Time Image Processing Approach to Measure Traffic Queue Parameters. Vision, Image and Signal Processing, IEEE  Proceedings – 142(5):297-303.
  8. Findler, N.V. et al, (1997). Distributed Intelligent Control of Street and Highway Ramp Traffic Signals. Engineering Applications of Artificial Intelligence 10(3): 281-292.
  9. Ganiyu R.A, et al, (2011) Modelling and Validation of Multi phase Intersection Using Timed Coloured Petrinets. American Journal of Scientific and Industrial Research Vol. 2, No 5, pp 807 – 819,
  10. Ganiyu R.A, et al, (2011), P-Invariant Analysis of Timed Coloured Petri Net Models of two Isolated Multi-Phase Traffic Light Controlled Intersections, International Journal of Applied Science and Technology Vol. 1 No 4 pp 29-41.
  11. Hashim N.M, et al, (2013), Traffic Light Control System for Emergency Vehicles Using Radio Frequency IOSR Journal of Engineering Vol. 3 No 7 pp 43-53.
  12. Huang, Q. and Miller, R (2004). Reliable Wireless Traffic Signal protocols for Smart Intersections
  13. Ifechi N.V, (2010) Design and Implementation of a Microcontroller based Versatile Y and Cross Junction Traffic Light Control System/Trainer "An M-Eng Thesis in Electronics and Computer Engineering, Nnamdi Azikwe University, Awka Nigeria.
  14. Ingalls, R.G, Eckersley, C. (1992) Simulation Issues in Electronics Manufacturing, Proceedings of the Winter.
  15. Ingalls, R.G., (1998). The Value of Simulation in Modeling Supply Chains. Proceedings of the Winter Simulation Conference. Ed. D.J. Mediros, E.F Watson, J.S. Cartson, and M.S. Manivannan. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers.
  16. Law, A.M, and Kelton, W.D. (2000). Simulation Modeling and Analysis, 3rd Ed., McGraw-Hill.
  17. Lei, J. and Ozguner, U. (1999). Combined Decentralized Multi-Destination Dynamic Routing and Real Time Traffic Light Control for Congested Traffic Networks.
  18. Mbakwike N . (2007). 7 Million Vehicles Operate on Nigerian Roads FRSC Leadership Newspaper, 16th November 2007.
  19. Raje Swani S. Design of Sophisticated Traffic Light Control System; Middle East Journal of Scientific Research Vol. 12 pp 1547 – 1652, 2014.
  20. Tavladakis, A.K. (1999). Development of an Autonomous Adaptive Traffic Control System. European Symposium on Intelligent Techniques.
  21. Ugwu, C. (2009), Nigeria Over Seven Million Vehicles Ply Nigerian Road, Daily Filani Champion Newspapers, Nigeria 2nd October 2009.
  22. Zade A.R and Dandekar (2011), FPGA Implementation of Intelligent Traffic Signal Controller Based on Macro Fuzzy System, International Conference on Advanced Computing Communication and Networks pp 1310-1314.

Publication Details

Published in : Volume 2 | Issue 6 | November-December - 2016
Date of Publication Print ISSN Online ISSN
2016-12-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
581-583 IJSRSET1626153   Technoscience Academy

Cite This Article

Eze M. N., Uchegbu C. E., Ilo F. U., Ugwu O. C., "Development of Traffic Flow in a Mega City Using Neural Network Controller", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 6, pp.581-583, November-December-2016.
URL : http://ijsrset.com/IJSRSET1626153.php